Unequal Partners? Local Government Reorganization and the Voluntary Sector

British local government has recently undergone its most far-reaching reorganization for twenty-five years. The impact of this reorganization was considerable within local authorities but it also substantially affected other organizations with which they worked at a local level. This paper explores the perspectives of voluntary sector organizations involved in social care: a set of actors which, prior to reorganization, had been encouraged by central and local government, through notions of partnership and through community care legislation, to undertake more direct roles in service delivery, consultation and strategic planning. During the consultative period prior to reorganization, many voluntary organizations reported that they had been marginal to the process. Reflecting on the process of reorganization itself, many voluntary organization respondents commented that it had been disruptive and provoked considerable anxiety. Post-reorganization, voluntary organizations felt that rebuilding of relationships was necessary and that the promise of partnership had meant little in practice at a time of potential crisis for local.     

Career Decision State and Assessment of RIASEC Interest Structure

The career decision state (CDS) was studied in relation to RIASEC (Realistic, Investigative, Artistic, Social, Enterprising, Conventional) profiles in Self-Directed Search results among college students (86 women, 27 men). Three CDS dimensions measured by the Career State Inventory (CSI; certainty, satisfaction, and clarity) were examined as predictors of RIASEC primary and secondary constructs. Significant, albeit modest, zero-order correlations (p < .05) emerged between clarity and 3 secondary constructs (i.e., consistency, commonness, and coherence). Results of regression analyses indicated that CSI dimensions predicted 1 secondary construct (i.e., commonness).     

Restaurant Revenue Management at Chevys: Determining the Best Table Mix

Revenue management has been used in a variety of industries and generally takes the form of managing demand by manipulating length of customer usage and price. Supply mix is rarely considered, although it can have considerable impact on revenue. In this research, we focused on developing an optimal supply mix, specifically on determining the supply mix that would maximize revenue. We used data from a Chevys restaurant, part of a large chain of Mexican restaurants, in conjunction with a simulation model to evaluate and enumerate all possible supply (table) mixes. Compared to the restaurant's existing table mix, the optimal mix is capable of handling a 30% increase in customer volume without increasing waiting times beyond their original levels. While our study was in a restaurant context, the results of this research are applicable to other service businesses.     

Country-specific institutional effects on ownership: concentration and performance of continental European firms

This paper examines the effect of country-specific institutional constructs on the relationship between ownership concentration and performance for firms in the eight Continental European countries of Austria, Belgium, Germany, Spain, France, Italy, the Netherlands and Portugal. Using data from publicly-traded firms owned by other companies (i.e., blocks), measures of the quality of investor and creditor protection and the effectiveness of legal institutions are applied. Employing a hierarchical moderated multiple regression analysis, differential validity is established for the relationship between ownership concentration and performance as measured by return on shareholders’ funds. This differential effect comes from creditor protection regimes and is consistent with a relational corporate governance model based on debt finance and concentrated ownership.     

Effects of repeated multi-source feedback on the influence behavior and effectiveness of managers: A field experiment

Despite the widespread use of multi-source behavioral feedback as a method of leadership development, little research has been conducted to identify facilitating conditions that can make the feedback more effective. This article reports results from a longitudinal field experiment on the effects of providing feedback about influence behavior to middle managers in the corporate office of a supermarket chain. Managers who only attended a single feedback workshop were compared to managers who attended a second feedback workshop several months after the initial one. A significant increase in the use of “core” influence tactics with subordinates and peers was found only for the managers who received repeated feedback, and they were also rated higher in overall effectiveness by their bosses. Practical implications for leadership development and suggestions for future research are discussed.     

Binary Response Models for Panel Data: Identification and Information

This paper considers a panel data model for predicting a binary outcome. The conditional probability of a positive response is obtained by evaluating a given distribution function (F) at a linear combination of the predictor variables. One of the predictor variables is unobserved. It is a random effect that varies across individuals but is constant over time. The semiparametric aspect is that the conditional distribution of the random effect, given the predictor variables, is unrestricted. This paper has two results. If the support of the observed predictor variables is bounded, then identification is possible only in the logistic case. Even if the support is unbounded, so that (from Manski (1987)) identification holds quite generally, the information bound is zero unless F is logistic. Hence consistent estimation at the standard pn rate is possible only in the logistic case.     

The Association of Knowledge with Concern About Global Warming: Trusted Information Sources Shape Public Thinking

During the last decade, a great deal of news media attention has focused on informing the American public about scientific findings on global warming (GW). Has learning this sort of information led the American public to become more concerned about GW? Using data from two surveys of nationally representative samples of American adults, this article shows that the relation between self‐reported knowledge and concern about GW is more complex than what previous research has suggested. Among people who trust scientists to provide reliable information about the environment and among Democrats and Independents, increased knowledge has been associated with increased concern. But among people who are skeptical about scientists and among Republicans more knowledge was generally not associated with greater concern. The association of knowledge with concern among Democrats and Independents who trust scientists was mediated by perceptions of consensus among scientists about GW's existence and by perceptions that humans are a principal cause of GW. Moreover, additional analyses of panel survey data produced findings consistent with the notion that more knowledge yields more concern among Democrats and Independents, but not among Republicans. Thus, when studying the relation of knowledge and concern, it is important to take into account the content of the information that different types of people acquire and choose to rely upon.     

Decision Theory Applied to a Linear Panel Data Model

This paper applies some general concepts in decision theory to a linear panel data model. A simple version of the model is an autoregression with a separate intercept for each unit in the cross section, with errors that are independent and identically distributed with a normal distribution. There is a parameter of interest γ and a nuisance parameter τ, a N×K matrix, where N is the cross‐section sample size. The focus is on dealing with the incidental parameters problem created by a potentially high‐dimension nuisance parameter. We adopt a “fixed‐effects” approach that seeks to protect against any sequence of incidental parameters. We transform τ to (δ, ρ, ω), where δ is a J×K matrix of coefficients from the least‐squares projection of τ on a N×J matrix x of strictly exogenous variables, ρ is a K×K symmetric, positive semidefinite matrix obtained from the residual sums of squares and cross‐products in the projection of τ on x, and ω is a (N−J) ×K matrix whose columns are orthogonal and have unit length. The model is invariant under the actions of a group on the sample space and the parameter space, and we find a maximal invariant statistic. The distribution of the maximal invariant statistic does not depend upon ω. There is a unique invariant distribution for ω. We use this invariant distribution as a prior distribution to obtain an integrated likelihood function. It depends upon the observation only through the maximal invariant statistic. We use the maximal invariant statistic to construct a marginal likelihood function, so we can eliminate ω by integration with respect to the invariant prior distribution or by working with the marginal likelihood function. The two approaches coincide. Decision rules based on the invariant distribution for ω have a minimax property. Given a loss function that does not depend upon ω and given a prior distribution for (γ, δ, ρ), we show how to minimize the average—with respect to the prior distribution for (γ, δ, ρ)—of the maximum risk, where the maximum is with respect to ω. There is a family of prior distributions for (δ, ρ) that leads to a simple closed form for the integrated likelihood function. This integrated likelihood function coincides with the likelihood function for a normal, correlated random‐effects model. Under random sampling, the corresponding quasi maximum likelihood estimator is consistent for γ as N→∞, with a standard limiting distribution. The limit results do not require normality or homoskedasticity (conditional on x) assumptions.